from model import Model
from pySAXS.LS.LSsca import Qlogspace
from pySAXS.LS.LSsca import *
import numpy
[docs]class Pcylmultimin(Model):
'''
Multilayer Cylinder
by OT 10/06/2009
'''
[docs] def PcylmultiminFunction(self,q,par):
R=[par[0],par[1],par[2],par[3],par[4],par[5]]
rho=[par[6],par[7],par[8],par[9],par[10],par[11],par[12]]
L=par[13]
rhos=par[14]
return self.Pcylmulti(q,R,rho,L,rhos)
[docs] def Pcylmulti(self,q,R,rho,L,rhos):
"""
This function calculates the P(q) of a cylinder of length L and and multilayers R of density Rho the last one being solvent
"""
Pcylnew=1.*q
Pcylold=1.*q
for i in range(len(q)):
N=1.
alpha0=1e-12
alphaN=pi/2
#----------------------------------------------------------------------------------------------------
"""Somme sur les ecorces"""
dPeco=0.
for j in range(len(R)):
dPeco=dPeco+(rho[j]-rho[j+1])*(2.*R[j]*SPspecial.j1(q[i]*R[j]*numpy.sin(alpha0))/(q[i]*numpy.sin(alpha0)))
dPcyl0=numpy.sin(alpha0)*(numpy.sin(q[i]*L*numpy.cos(alpha0)/2.)/(q[i]*L*numpy.cos(alpha0)/2.)*dPeco)**2
#----------------------------------------------------------------------------------------------------
dPeco=0.
for k in range(len(R)):
dPeco=dPeco+(rho[k]-rho[k+1])*(2.*R[k]*SPspecial.j1(q[i]*R[k]*numpy.sin(alphaN))/(q[i]*numpy.sin(alphaN)))
dPcylN=numpy.sin(alphaN)*(numpy.sin(q[i]*L*numpy.cos(alphaN)/2.)/(q[i]*L*numpy.cos(alphaN)/2.)*dPeco)**2
#----------------------------------------------------------------------------------------------------
dPcylold=(dPcyl0+dPcylN)/2.
Pcylold[i]=pi/2*dPcylold
test=1.
while(abs(test)>1e-4):
N=2.*N
dalpha=(pi/2.-alpha0)/N
alpha=numpy.arange(dalpha,pi/2.,2.*dalpha)
#----------------------------------------------------------------------------------------------------
dPeco=0.*alpha
for l in range(len(R)):
dPeco=dPeco+(rho[l]-rho[l+1])*(2.*R[l]*SPspecial.j1(q[i]*R[l]*numpy.sin(alpha))/(q[i]*numpy.sin(alpha)))
dPcyl=numpy.sin(alpha)*(numpy.sin(q[i]*L*numpy.cos(alpha)/2.)/(q[i]*L*numpy.cos(alpha)/2.)*dPeco)**2
#----------------------------------------------------------------------------------------------------
dPcylnew=sum(dPcyl)+dPcylold
dPcylold=dPcylnew
Pcylnew[i]=dalpha*dPcylnew
test=(Pcylnew[i]-Pcylold[i])/Pcylold[i]
Pcylold[i]=Pcylnew[i]
return Pcylold*numpy.pi**2*L**2*1e-48*rhos
'''
parameters definition
Model(10,Pcylmultimin,Qlogspace(1e-4,1.,500.),
([13.,14.,15.,16.,17.,18.,9.418e+010,8.798e+010,4.041e+011,3.925e+011,4.224e+011,3.902e+011,9.418e+010,400.,1e17]),
("R1 (A)","R2 (A)","R3 (A)","R4 (A)","R5 (A)","R6 (A)","rho1 (cm-2)","rho2 (cm-2)","rho3 (cm-2)","rho4 (cm-2)","rho5 (cm-2)","rho6 (cm-2)","rho7 (cm-2)","L (A)","Rhos (cm-3)"),
("%1.3e","%1.3e","%1.3e","%1.3e","%1.3e","%1.3e","%1.3e","%1.3e","%1.3e","%1.3e","%1.3e","%1.3e","%1.3e","%1.3e","%1.3e"),
(True,True,True,True,True,True,True,True,True,True,True,True,True,True,True))]
from LSsca
'''
IntensityFunc=PcylmultiminFunction #function
N=0
q=Qlogspace(1e-4,1.,500.) #q range(x scale)
Arg=[13.,14.,15.,16.,17.,18.,9.418e+010,8.798e+010,4.041e+011,3.925e+011,4.224e+011,3.902e+011,9.418e+010,400.,1e17] #list of defaults parameters
Format=["%1.3e","%1.3e","%1.3e","%1.3e","%1.3e","%1.3e","%1.3e","%1.3e","%1.3e","%1.3e","%1.3e","%1.3e","%1.3e","%1.3e","%1.3e"] #list of c format
istofit=[True,True,True,True,True,True,True,True,True,True,True,True,True,True,True] #list of boolean for fitting
name="Multilayer Cylinder" #name of the model
Doc=["R1 (A)","R2 (A)","R3 (A)","R4 (A)","R5 (A)","R6 (A)","rho1 (cm-2)","rho2 (cm-2)","rho3 (cm-2)","rho4 (cm-2)","rho5 (cm-2)","rho6 (cm-2)","rho7 (cm-2)","L (A)","Rhos (cm-3)"] #list of description for parameters
if __name__=="__main__":
'''
test code
'''
modl=Pcylmultimin()
#plot the model
import Gnuplot
gp=Gnuplot.Gnuplot()
gp("set logscale xy")
c=Gnuplot.Data(modl.q,modl.getIntensity(),with_='points')
gp.plot(c)
raw_input("enter")
#plot and fit the noisy model
yn=modl.getNoisy(0.4)
cn=Gnuplot.Data(modl.q,yn,with_='points')
res=modl.fit(yn)
cf=Gnuplot.Data(modl.q,modl.IntensityFunc(modl.q,res),with_='lines')
gp.plot(c,cn,cf)
raw_input("enter")
#plot and fit the noisy model with fitBounds
bounds=modl.getBoundsFromParam() #[250.0,2e11,1e10,1.5e15]
res2=modl.fitBounds(yn,bounds)
print res2
raw_input("enter")